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about.md

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---
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site:
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hide_toc: true
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---
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# About
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<!--
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# Statistical Python: Bridging Statistical Methods and Software Engineering
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"""
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-->
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The Statistical Python project was launched with support from a [POSE Phase I grant from the NSF](https://nsf.elsevierpure.com/en/projects/pose-phase-1-an-open-source-ecosystem-for-statistical-python), titled "POSE: Phase I: An open-source ecosystem for statistical Python."
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This initiative seeks to catalyze the development of robust statistical software for Python and to build a vibrant ecosystem of statisticians, domain practitioners, educators, and software developers.
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Our vision is to foster a community that bridges the gap between statistical innovation and open-source software engineering, informed by best practices from both the Python and R communities.
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We are now completing Phase I, which has focused on scoping activities to inform the transition into a sustainable open-source ecosystem.
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During this phase, we have conducted a series of interviews with stakeholders across the statistical and scientific Python communities, engaged with related domain-stack OSEs to learn from their experiences, and organized a workshop to gather input on community needs and technical directions.
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Based on our [2024 Landscape Analysis](2024-landscape), we ...
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-->

index.md

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---
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title: Welcome to Statistical Python
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site:
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---
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## Welcome to Statistical Python
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# Welcome to Statistical Python
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The Statistical Python project is a community-driven and community-owned initiative dedicated to building a robust, sustainable ecosystem for statistical software in Python.
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Our mission is to unite statisticians, domain practitioners, educators, and software developers to create high-quality, well-engineered statistical tools that empower research, education, and industry.
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By fostering collaboration and knowledge sharing, we aim to lower barriers to contribution, promote best practices in software engineering, and ensure that cutting-edge statistical methods are accessible to the broader Python community.
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As a domain stack within the larger [Scientific Python project](https://scientific-python.org/), Statistical Python leverages the strengths of the scientific Python ecosystem while addressing the unique needs of the statistical community.
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Supported by an NSF POSE Phase I grant, our work focuses on bridging the gap between innovative statistical methodology and modern open-source software development.
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Our vision is to foster a community that bridges the gap between statistical methodology and modern open-source software engineering, drawing on best practices from both the Python and R communities.
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Our goal is to catalyze the growth of a vibrant, cross-disciplinary developer and user base, making Python a premier platform for statistical computing and education.

myst.yml

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# description:
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# keywords: []
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# authors: []
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# github: https://github.com/statistical-python/statistical-python.org
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github: https://github.com/statistical-python/
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# To autogenerate a Table of Contents, run "myst init --write-toc"
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site:
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template: book-theme
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#nav:
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# - title: Packages
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# url: /packages
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nav:
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- title: About
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url: /about
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- title: Packages
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url: /packages
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options:
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favicon: images/favicon.ico
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logo: images/statistical-python-logo.svg

packages.md

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title: Packages
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---
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# Packages
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# Pilot Projects
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As part of our NSF-funded initiative, we're working with two pilot projects that represent different aspects of the statistical Python ecosystem:
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- **[YAGLM](https://github.com/yaglm/yaglm)**: A Python package for generalized linear models that provides modern statistical methodology with various loss functions, regularizers, and solvers.
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- **[ISLP](https://github.com/intro-stat-learning/ISLP)**: A companion Python package for the textbook "An Introduction to Statistical Learning with Applications in Python," focused on educational resources and implementations.

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